Macht man sich die Mühe einer ernsthaften Analyse des e-Learning, so stellt man fest, dass die Verheißungen sich oft noch nicht erfüllt haben. Die Frage danach, wie e-Learning erfolgreich sein kann, wird in dem Maß wichtiger, in dem wir uns von einer
Suchmaschinen benötigen trotz ausgefeilter Algorithmen menschliche Bewerter der Suchresultate. Ein ziemlich aktueller Leitfaden vom März 2011 erklärt, wie Quality Rater gegen Spam vorgehen sollen und die Nützlichkeit von Webseiten einschätzen. Falls eine Seite nur dafür existiert Geld zu machen, ist die Seite Spam. . Die PDF-Datei der Rating Guidelines ist mit dem Datum 30.März 2011 [...]
AQUA - Automatic Quality Assessment and Feedback in eLearning 2.0
The current development of Web 2.0 makes the distinction between author and reader fading away. Users now produce huge amounts of data which sometimes is of questionable quality. This leads to the problem of information overload: how to make the most of this information without overwhelming the users? One key challenge to solve this issue is to assess the quality of the user generated content.
In AQUA, we seek to develop algorithms to assess the quality of content automatically. We focus on two sources for this assessment: (1) user generated content; (2) feedback by users of the content. To do so, we investigate techniques from the fields of natural language processing (NLP), information retrieval, and machine learning.
So, in a nutshell, AQUA will answer the following questions:
What is quality of information? How does it matter in information search?
How to model the quality of user generated content?
How far can you go with automatic methods in assessing quality?
How to give feedback to users regarding quality?
The AQUA project is associated with the project "Mining Lexical-Semantic Knowledge from Dynamic and Linguistic Sources and Integration into Question Answering for Discourse-Based Knowledge Acquisition in e-learning (QA-EL)".
SONAR is an open source quality management platform, dedicated to continuously analyze and measure source code quality, from the portfolio to the method.
Xively is a secure platform for Internet of Things devices and products. Its API and web service provide real-time control and data storage. Bring connected products to market using our provisioning service. Set alerts, collaborate and exchange data.
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